Real Size Research Articles

Grain size estimation in polycrystals: Solving the corpuscle problem using Maximum Likelihood Estimation

In materials science, the microstructures of materials are generally characterized by 2D observation (e.g. electron microscopy). For polycrystalline materials, such as crystalline rocks or ceramics, those observations can be used to measure the grain size distribution. However, the fact that grain sizes are measured in planar cuts introduces a statistical bias, since the real (3D) grain sizes cannot be directly measured. For almost spherical grains, this bias can be computed thanks to the so-called Wicksell's equation. This paper proposes a method, based on Maximum Likelihood Estimation (MLE) for unfolding the apparent 2D distribution. The efficiency of this method is extensively investigated in the special case of lognormal distribution. In this case, 10% uncertainty on the distribution parameters can be reached with only 580 empirical values.

Integrated population models poorly estimate the demographic contribution of immigration

Abstract Estimating the contribution of demographic parameters to changes in population growth is essential for understanding why populations fluctuate. Integrated population models (IPMs) offer a possibility to estimate the contributions of additional demographic parameters, for which no data have been explicitly collected—typically immigration. Such parameters are often subsequently highlighted as important drivers of population growth. Yet, accuracy in estimating their temporal variation, and consequently their contribution to changes in population growth rate, has not been investigated. To quantify the magnitude and cause of potential biases when estimating the contribution of immigration using IPMs, we simulated data (using northern wheatear Oenanthe oenanthe population estimates) from controlled scenarios to examine potential biases and how they depend on IPM parameterization, formulation of priors, the level of temporal variation in immigration and sample size. We also used empirical data on populations with known rates of immigration: Soay sheep Ovis aries and Mauritius kestrel Falco punctatus with zero immigration and grey wolf Canis lupus in Scandinavia with near‐zero immigration. IPMs strongly overestimated the contribution of immigration to changes in population growth in scenarios when immigration was simulated with zero temporal variation (proportion of variance attributed to immigration = 63% for the more constrained formulation and real sample size) and in the wild populations, where the true number of immigrants was zero or near‐zero (kestrel 19.1%–98.2%, sheep 4.2%–36.1% and wolf 84.0%–99.2%). Although the estimation of the contribution of immigration in the simulation study became more accurate with increasing temporal variation and sample size, it was often not possible to distinguish between an accurate estimation from data with high temporal variation versus an overestimation from data with low temporal variation. Unrealistically, large sample sizes may be required to estimate the contribution of immigration well. To minimize the risk of overestimating the contribution of immigration (or any additional parameter) in IPMs, we recommend to: (a) look for evidence of variation in immigration before investigating its contribution to population growth, (b) simulate and model data for comparison to the real data and (c) use explicit data on immigration when possible.

What does COVID-19 testing results really say? The real statistics concealed behind the accessible data.

Accurate and comprehensive testing is crucial for practitioners to portray the pandemic. Without testing there is no data; yet, the exact number of infected people cannot be determined due to the lack of comprehensive testing. The number of seropositive for SARS‐CoV‐2 infection is obviously relative to the extent of testing. However, the true number of infections might be still far higher than the reported values. To compare the countries based on the number of seropositive for SARS‐CoV‐2 infection is misleading, as there may not be enough tests being carried out to properly monitor the outbreak. In this paper, we closely look through the COVID‐19 testing results. Herein, we try to draw conclusions based on the reported data: first, the presence of a possible relationship between COVID‐19 transition and patients' age will be assessed. Then, the COVID‐19 case fatality rate (CFR) is compared with the age‐demographic data for different countries. Based on the results, a method for estimating a lower bound (minimum) for the number of actual positive cases will be developed and validated. Results of this study have shown that CFR is a metric reflecting the spread of the virus, but is a factor of the extent of testing and does not necessarily show the real size of the outbreak. Moreover, no large difference in susceptibility by age has been found. The results suggest the similarity between the age distribution of COVID‐19 and the population age‐demographic is improving over the course of the pandemic. In addition, countries with lower CFRs have a more similar COVID‐19 age distribution, which is a result of more comprehensive testing. Finally, a method for estimation of the real number of infected people based on the age distributions, reported CFRs, and the extent of testing will be developed and validated.

Use of a real-life practical context changes the relationship between implicit body representations and real body measurements

A mismatch exists between people’s mental representations of their own body and their real body measurements, which may impact general well-being and health. We investigated whether this mismatch is reduced when contextualizing body size estimation in a real-life scenario. Using a reverse correlation paradigm, we constructed unbiased, data-driven visual depictions of participants’ implicit body representations. Across three conditions—own abstract, ideal, and own concrete body—participants selected the body that looked most like their own, like the body they would like to have, or like the body they would use for online shopping. In the own concrete condition only, we found a significant correlation between perceived and real hip width, suggesting that the perceived/real body match only exists when body size estimation takes place in a practical context, although the negative correlation indicated inaccurate estimation. Further, participants who underestimated their body size or who had more negative attitudes towards their body weight showed a positive correlation between perceived and real body size in the own abstract condition. Finally, our results indicated that different body areas were implicated in the different conditions. These findings suggest that implicit body representations depend on situational and individual differences, which has clinical and practical implications.

Surface Charge Accumulation on a Real Size Epoxy Insulator With Bouncing Metal Particle Under DC Voltage

Free metal particle can affect surface charge accumulation on epoxy insulator installed in gas-insulated transmission line (GIL) or gas-insulated switchgear (GIS), which results in reduction of surface flashover voltage thus threatening the safe operation of the power equipment. This article reports on the charge accumulation behavior on a real size epoxy insulator with bouncing metal particle under DC voltage. A coaxial electrode system was designed for the test under -30 kV, a metal particle-launching system was employed to inject the bouncing linear particle to the insulator surface. The charge distribution was measured by a Kelvin-type probe, and the influence of the particle on the charge accumulation was analyzed with the help of electric field simulation. The results showed that there were mainly two moving patterns of the bouncing particle: the charges were accumulated with speckle shape and the charged particle that hit the edge of electrode had more remarkable influence on the charge accumulation than other particles. It is suggested that the charge distribution feature is dependent upon the collision point and the trajectory of the bouncing particle.

Molecular dynamic and in vitro evaluation of chitosan/tripolyphosphate nanoparticles as an insulin delivery system at two different pH values

Understanding the atomic interaction mechanism between chitosan and insulin at different pH levels is essential in the design of chitosan-based drug-delivery systems. In the present study, insulin-loaded nanoparticles were prepared via ionic gelation of tripolyphosphate (TPP) and chitosan with 76 ± 5.5% encapsulation efficiency. Our results showed that the nanoparticles were spherical with a size of 254 nm. Furthermore, the in vitro release profile of insulin was evaluated for two different pH levels. The release of insulin from nanoparticles after 48 h at pH 4.0 was 92%, compared to 56% at pH 7.4. The kinetics of the release were best fitted by the Weibull equation, which described a burst release in the first five hours followed by a sustained insulin release for up to 48 h. Moreover, we designed a long single chain chitosan (128 kDa)/TPP nanoparticles in real size for the first time and studied the system behavior in acidic and neutral environments using molecular dynamic simulation for 40 nanoseconds (ns). Our results showed that chitosan chains opened more with higher root-mean-square deviation (RMSD) values at pH 4.0 than at pH 7.4. Also, RMSD plots for insulin and TPP molecules showed that insulin molecules diffused away from chitosan chains, and that TPP were randomly dispersed further away from the chitosan chain in an acidic medium than in a neutral one. The in silico studies were in agreement with our in vitro data. Thus self-assembled chitosan/TPP nanoparticles show promise as a means to release protein drugs in acidic environments. Communicated by Ramaswamy H. Sarma

Comparison of different forming methods on deep drawing and springback behavior of high-strength aluminum alloys

High-strength aluminum alloys of the 7XXX series have a high potential for safety and crash-relevant components due to their advantageous density-to-strength ratio. Currently, the use of these alloys is limited because of the low formability at room temperature. By using thermal supported forming strategies, failure-free deep drawing is possible for these materials. At present, several thermal-assisted forming processes exist, but so far there is no comparison between these forming operations. For this purpose, this study compares the deep drawing behavior of the alloy AA7075 by using different thermally-assisted forming operations. Aim of this work is to enhance the understanding and comparability between different thermally-assisted forming processes for high-strength aluminum alloys. First, a thermal simulator is used to investigate the mechanical material behavior according to different temperature-time curves by using uniaxial tensile tests. Subsequently, the formability and springback behavior is determined numerically and experimentally in a model test. Finally, for one thermally assisted forming method, the experiments are scaled up to a real size process with drawbeads to validate the transferability. This study can help to improve the scientific knowledge for the use of these materials in future.

Push-over bending and shear behavior assessments of hidden boundary void precast concrete slab with bi-tensional prestress

This paper presents a first proposed real-sized Hidden boundary Void precast concrete Slab, a so-called HVS. In order to assess and investigate push-over behaviors of the novel structural system, five types of real size specimens manufactured in factory are tested by corresponding static loading protocol experiments. Bending tests along with shear tests in both cases of presence and absence of topping concrete slabs are performed. Besides, composite slabs, which are two half-unit products connected by steel plates and U-bolts in the long edges, are surveyed to assess uniform characteristics of slab systems. Simultaneously, estimating calculations are proposed for the structural bearing capacity of partially prestressed concrete flagged sections. Proposed equations are developed according to provisions of several current global and local design standards. Moreover, this study provides another predicting approach using finite element analysis of MIDAS FEA for analytical performances of specimens. Thanks to these experimental and analytical results, the general characteristic of HVS may be observed, and then studied for realization in the field of prestressed precast concrete industries for construction.

(Gordon E. Moore Award) Impact of Micro-/Nano-Electronics, Miniaturization Limit, and Technology Development for the Next 10 Years and After

Impact of micro-/nano-electronics Electronics started at the beginning of the 20th century with the invention of vacuum tubes. It brought about modern technologies such as telecommunication, broadcast (radio/TV), computer, etc., and changed our society revolutionarily. Then, vacuum tubes were gradually replaced by semiconductor devices in the 1960’s, because of the advantage in cost, size and performance. Since then, the semiconductor devices have been continuously miniaturized. At the beginning of 1970’s, their feature device-size decreased to 10 μm and the number of the MOSFETs in a chip exceeded 1,000. This was the beginning of micro-electronics offering us Large-Scale Integrated Circuits (LSIs) such as microprocessors. Now, the feature device-size has reached the 10 nm-range and we call it nano-electronics. Micro-/nano-electronics has brought up new technologies such as internet, smart phones, artificial intelligence, virtual reality, robots, etc., and is changing our society towards the ultimately intelligent one.Miniaturization or the downsizing of electron devices such as the MOSFETs has been the key to improve the cost and performance. Today, 1T-bit (or 128G-Bite) SD cards composed of semiconductor memories are available with reasonable price. Let us imagine the world only with old-style vacuum tubes. Then, a 1T-bit memory with 1 trillion vacuum tubes would cost 100 trillion Japanese yen (or 1 trillion US dollars); the amount of Japan’s national budget, occupy the volume of 0.5 X 0.5 X 1.0 km3; larger than the world-tallest building, weigh 100M ton; the weight of 20 million elephants, and consume 5T Watt; the generated power of 5,000 nuclear reactors, and 4 X 1020 calorie energy in a year; 2,000 times as large as the energy of yearly global human consumption. So, without the development of micro-/nano-electronics, today’s smart society with internet, artificial intelligence, etc. does not exist, and thus, the invention of micro-/nano-electronics is the biggest technological revolution after that of electronics. Limit of miniaturization What is the limit of miniaturization? There are 3 stages of the limit. The first one is the ‘ultimate limit’, which is defined by the distance of atoms in the material; about 0.3 nm in the Si substrate case. Changing material does not make a big difference. No one can make the device structures less than the atomic distance. So, it should be noted that there is no ‘pico-electronics’ anymore next to the nano-electronics.Before reaching the ultimate limit, there is another limit, named ‘fundamental limit’ which is defined by the direct-tunneling distance; about 3 nm. When the distance between the structures becomes 3 nm, the wavefunction of the materials penetrates the potential barrier between the structures, and huge direct-tunneling current starts to flow. So, there is no electrical insulation or switching-off of the devices. Thus, 3 nm is the limit for the device operation.The third limit is a ‘practical limit’ defined by the demerit of downsizing; about 10 ~ 20 nm. When the demerit of the downsizing becomes larger than the merit, then the downsizing will stop. The demerit may be the degradations in off-leakage current, production cost, reliability, and variability of the device characteristics, and so on. Recently, logic devices with the commercial names of ‘7 nm’ or ‘5 nm’ technology are in production. However, it should be noted that those sizes used in the commercial names of the logic devices have nothing to do with the real sizes, which are typically 30 ~ 15 nm for the minimum line widths. Then, what would be the limit of the downsizing? Off-leakage current or subthreshold leakage current between the source and drain of the MOSFET is regarded as the one of the main causes of the limit for the downsizing, because we cannot suppress the diffusion of electrons from the source to the channel (which is defined by Boltzmann statistics) unless changing the device operation temperature to extremely low such as 77K. However, it is difficult for the majority of the market. So, it is the consensus that the channel length is difficult to reach sub-10 nm for the major market devices. Future technology development in next 10 years and after that Although we are very close to the limit, we have to continue to develop the new technologies towards its limit, because nano-electronics is the key for today’s smart society and the demand from the market is so strong. The new technologies are 3D integration, new materials for interconnects, resolution improvement of EUV lithography, etc. Even, the limit of the downsizing is approaching, we will have so many things to do in the next 10 years and even after that.

Solving group multi-objective optimization problems by optimizing consensus through multi-criteria ordinal classification

In this paper good consensus is associated with a high level of group satisfaction and a low level of dissatisfaction. A new method to improve consensus through a reformulation of the original group multi-objective optimization problem is introduced. For each point in the feasible decision set, the level of satisfaction or dissatisfaction from each group member is determined by multi-criteria ordinal classification approaches. Intense satisfaction and dissatisfaction are both modeled. Group satisfaction (respectively, dissatisfaction) is maximized (resp. minimized), finding the best possible consensus solutions in correspondence with a current stage of closeness among group members’ preferences, judgments, beliefs, and conservatism attitudes. Logic models are introduced to evaluate conditions for best consensus. Imperfect information (imprecision, uncertainty, ill-definition, arbitrariness) on the values of objective functions, required and available resources, and decision model parameters is handled by using interval numbers. Two different kinds of multi-criteria decision model are considered: i) an interval outranking approach and ii) an interval weighted-sum value function. The proposal can handle very general cases of group multi-objective optimization problems. The method is illustrated by solving a real size multi-objective project portfolio optimization problem using evolutionary computation tools.

A FEM-Based 2D Model for Simulation and Qualitative Assessment of Shot-Peening Processes.

Shot peening is one of the most favored surface treatment processes mostly applied on large-scale engineering components to enhance their fatigue performance. Due to the stochastic nature and the mutual interactions of process parameters and the partially contradictory effects caused on the component’s surface (increase in residual stress, work-hardening, and increase in roughness), there is demand for capable and user-friendly simulation models to support the responsible engineers in developing optimal shot-peening processes. The present paper contains a user-friendly Finite Element Method-based 2D model covering all major process parameters. Its novelty and scientific breakthrough lie in its capability to consider various size distributions and elastoplastic material properties of the shots. Therewith, the model is capable to provide insight into the influence of every individual process parameter and their interactions. Despite certain restrictions arising from its 2D nature, the model can be accurately applied for qualitative or comparative studies and processes’ assessments to select the most promising one(s) for the further experimental investigations. The model is applied to a high-strength steel grade used for automotive leaf springs considering real shot size distributions. The results reveal that the increase in shot velocity and the impact angle increase the extent of the residual stresses but also the surface roughness. The usage of elastoplastic material properties for the shots has been proved crucial to obtain physically reasonable results regarding the component’s behavior.

Topological-Based Measures with Flow Attributes to Identify Critical Links in a Transportation Network

An important part of transportation network vulnerability analysis is identifying critical links where failure may lead to severe consequences, and the potential of such incidents cannot be considered negligible. Existing transportation network vulnerability assessment can be categorized as topological, or traffic based. Topological-based assessment identifies the most critical components in the network by considering network structure and connectivity. Traffic-based assessment identifies the most critical components in the network by full-scan analysis and takes into consideration effects of link failures to traffic flow assignment. The former approach does not consider traffic flow dynamics and fails to capture the non-linearity performance function of transport systems while the latter, even though accurate and robust, requires significant computational power and time and may not always be feasible for real life size networks. The primary objective of this paper is to propose new link criticality measures and evaluate their accuracy for transportation network vulnerability assessment. These measures combine characteristics of traffic equilibrium and network topology to balance accuracy and computational complexity. Nine measures are proposed, and their accuracy is compared with three existing traffic-based measures using three case study transportation networks from the literature. Results indicate that three of the proposed measures show strong correlation to the three traffic-based measures while requiring significantly less computational power and time.

Metamaterials acoustic barrier

Metamaterials represent a new technology in noise control fields. The first studies about metamaterials date back to the 1900s. The ability to deflect acoustic waves is due to the geometric of the structures that generate resonance effects, and to the periodic arrangement within the material. In this paper, the sound attenuation of an acoustic barrier made with metamaterial was investigated. Compared to the real size, a 1:10 scale model was built using cylindrical wooden bars, 30 cm high and 1.5 cm in diameter. The barrier was investigated for different alternating rows of cylindrical bars, spacing each bar with an empty space to create regular geometries. The insertion loss of each configuration is reported in frequency domain. Furthermore, this configuration could be used for the realization of acoustic filters for the noise control of air conditioning systems (HVAC) and the noises generated by rotating elements.

A New Approach to Group Multi-Objective Optimization under Imperfect Information and Its Application to Project Portfolio Optimization

This paper addresses group multi-objective optimization under a new perspective. For each point in the feasible decision set, satisfaction or dissatisfaction from each group member is determined by a multi-criteria ordinal classification approach, based on comparing solutions with a limiting boundary between classes “unsatisfactory” and “satisfactory”. The whole group satisfaction can be maximized, finding solutions as close as possible to the ideal consensus. The group moderator is in charge of making the final decision, finding the best compromise between the collective satisfaction and dissatisfaction. Imperfect information on values of objective functions, required and available resources, and decision model parameters are handled by using interval numbers. Two different kinds of multi-criteria decision models are considered: (i) an interval outranking approach and (ii) an interval weighted-sum value function. The proposal is more general than other approaches to group multi-objective optimization since (a) some (even all) objective values may be not the same for different DMs; (b) each group member may consider their own set of objective functions and constraints; (c) objective values may be imprecise or uncertain; (d) imperfect information on resources availability and requirements may be handled; (e) each group member may have their own perception about the availability of resources and the requirement of resources per activity. An important application of the new approach is collective multi-objective project portfolio optimization. This is illustrated by solving a real size group many-objective project portfolio optimization problem using evolutionary computation tools.

Biochemical and technological characteristics of wooden breast chicken fillets and their consumer acceptance.

The wooden breast (WB) has caused great damages to meat producing industries, being its etiology still not fully understood. Thus, the objective of this work was to investigate biochemistry and technological characteristics of WB chicken fillets and their consumer acceptance. WB fillets were evaluated in regards to color, pH, approximate chemical composition, water holding capacity, cooking loss, shear force, total and soluble collagen, and comparison estimated of pyridinoline. The sensorial analysis used real size images of fillets. The WB showed changes in physical parameters such as an increase in luminosity and shear force. In regards to the chemical parameters, showed an increase in pH value, moisture content, lipids, and mineral, and protein content reduction. There were biochemistry changes in the collagen with an increase of 17.32% in total collage content and a reduction by 30.96% in the estimated pyridinoline content. Technological parameters were negatively altered by a reduction in water holding capacity. WB fillets showed a low acceptance rate and intention to purchase. Results show the WB meat presented biochemistry and technological characteristics compromised besides a low acceptance and purchase intention, leading to economic losses for the poultry sector.

Anatomy Learning under COVID‐19 Measures: A Real World Educational Experiment

IntroductionThe best way to teach human gross anatomy to medical students has often been debated, although recent studies emphasize on the benefits of dissection‐based courses (DOI 10.1002/ase.1859). Prosection and model‐based courses, online and virtual reality approaches have been introduced over time, due to reduction in teaching time, and due to economic reasons with decreasing budget. In 2020, we were challenged by the pandemic of SARS‐CoV‐2 and corresponding COVID‐19 public health measures. We had to change and adapt several times anatomy teaching and learning over the two semesters for the cohort of 112 first/second year undergraduate medical students. With the experience of this student cohort with various anatomy learning approaches, we wanted to know what anatomy teaching method was best perceived by the students.Methods112 medical students were asked about their learning experience with various anatomy teaching approaches for 2020, including 1) dissection‐based learning, 2) prosections and models‐based demonstrations, 3) structured self‐directed learning using written instructions and corresponding anatomical material, 4) structured self‐directed learning using online instructions via Moodle and an online anatomy program (https://e‐learn.anatomy.uzh.ch/Anatomy/Anatomy.html; German version). All students agreed to participate in the study. The questionnaire was administered by https://www.surveymonkey.com and done anonymously. To date 66/112 (59%) students replied.ResultsThe majority of the students (92%) preferred the dissection course as their main anatomy learning method, 80% of students were happy with a demonstration course using prosections and anatomical models. Only a minority liked to have structured self‐directed learning with either anatomical specimens and models (42%) or with online material (36%). Rather few students preferred learning with an online course (18%) or through unstructured self‐directed learning using their own resources (12%). For the dissection course the students appreciated the 3 dimensional aspect (92%), the real size appearance of the structures (90%), the active explorative approach (81%), the topographical relationship of the structures (81%) and anatomical variability (72%). During complete lock‐down of the COVID‐19 measures when the students had to stay isolated at home for several weeks, the majority of students thought that the offered online structured self‐directed course was most adequate under those circumstances (55%), but would otherwise not be the preferred replacement of a dissection course (55%).ConclusionEvaluation of student experience with a variety of anatomy learning methods clearly indicate that a structured dissection‐based course with additional anatomical demonstration would be preferred by the majority of our students. Online material would be beneficial as additional learning support. However, the majority of students agreed that, under strict COVID‐19 stay‐at‐home measures, the structured self‐directed online course was the best way to learn anatomy. When going back to normal, we will offer the newly developed online material for guided self‐directed learning, in addition to the established dissection course.

LVD-NMPC: A learning-based vision dynamics approach to nonlinear model predictive control for autonomous vehicles

In this article, we introduce a learning-based vision dynamics approach to nonlinear model predictive control (NMPC) for autonomous vehicles, coined learning-based vision dynamics (LVD) NMPC. LVD-NMPC uses an a-priori process model and a learned vision dynamics model used to calculate the dynamics of the driving scene, the controlled system’s desired state trajectory, and the weighting gains of the quadratic cost function optimized by a constrained predictive controller. The vision system is defined as a deep neural network designed to estimate the dynamics of the image scene. The input is based on historic sequences of sensory observations and vehicle states, integrated by an augmented memory component. Deep Q-learning is used to train the deep network, which once trained can also be used to calculate the desired trajectory of the vehicle. We evaluate LVD-NMPC against a baseline dynamic window approach (DWA) path planning executed using standard NMPC and against the PilotNet neural network. Performance is measured in our simulation environment GridSim, on a real-world 1:8 scaled model car as well as on a real size autonomous test vehicle and the nuScenes computer vision dataset.

Image‐based road crack risk‐informed assessment using a convolutional neural network and an unmanned aerial vehicle

Rapid crack assessment is widely thought to be critical for monitoring and maintaining roads in appropriate conditions. In this paper, a novel crack-affected risk-informed assessment framework is proposed for the monitoring and maintenance of roads. The framework includes five steps: data collection, crack detection, crack location extraction, crack real-size calculation, and risk-level assessment. To support the framework, an unmanned aerial vehicle (UAV) is used to monitor roads and collect data. A state-of-the-art semantic segmentation network, DeepLabv3+, is also applied to detect cracks. Based on the height and pixel statistics of the detected crack, the real size of the crack can be calculated using the pixel-physical conversion coefficient equation. This is followed by a risk-informed assessment of the road identifying the location of the crack for maintenance priority determination. Data collection and experiments using a UAV were performed on a real road to verify the feasibility and effectiveness of the proposed method. It was found that the proposed method was not only able to determine the real size of the cracks from the collected images but also able to determine their risk levels. In summary, this method presents a convenient and reliable solution for risk-informed road crack assessment that can be employed in practical applications.

Hot isostatic pressing assisted diffusion bonding for application to the Super Proton Synchrotron internal beam dump at CERN

The new generation internal beam dump of the Super Proton Synchrotron (SPS) at CERN will have to dissipate approximately 270 kW of thermal power, deposited by the primary proton beam. For this purpose, it is essential that the cooling system features a very efficient heat evacuation. Diffusion bonding assisted by Hot Isostatic Pressing (HIP) was identified as a promising method of joining the cooling circuits and the materials of the dump's core in order to maximise the heat transfer efficiency. This paper presents the investigation of HIP assisted diffusion bonding between two CuCr1Zr blanks enclosing SS 316L tubes and the realisation of a real size prototype of one of the dump's cooling plate, as well as the assessments of its cooling performance under the dumps most critical operational scenarios. Energy-dispersive X-ray (EDX) spectroscopy, microstructural analyses, measurements of thermal conductivity and mechanical strength were performed to characterize the HIP diffusion bonded interfaces (CuCr1Zr-CuCr1Zr and CuCr1Zr-SS316L). A test bench allowed to assess the cooling performance of the real size prototype. At the bonded interface, the presence of typical diffusional phenomena was observed. Moreover, measured tensile strength and thermal conductivity were at least equivalent to the lowest ones of the materials assembled and comparable to its bulk properties, meaning that a good bonding quality was achieved. Finally, the real size prototype was successfully tested with an ad-hoc thermal test bench and with the highest operational thermal power expected in the new generation SPS internal beam dump.

Mid-term redeployment of capacity of rescue centers considering the optimism of the decision maker

In this paper, we consider the problem of allocation of Emergency Vehicles (EVs) to Rescue Centers (RCs). The objective is to improve the operational response of the Fire and Rescue Services (SDIS) in France. More precisely, we focus on the mid-term management, and on the process of redeployment of EVs in RCs according to the evolution of requirements. At this level of decision, we do not have information on accidents. We only used the available information on the simultaneity of requirements. Based on the Hurwicz criterion, we develop a mathematical model and an iterative algorithm to solve it. The proposed approach takes into account both the uncertainty on the occurrence sequence of accidents, and the attitude towards optimization of the decision maker (DM). An illustration from the DM’s point of view is presented. It shows that this uncertainty significantly impacts the deployment of EVs. Results show that the proposed approach has an efficient resolution time for real size problems.